Overlay multicast has become one of the most promising multicast solutions for IP network,and Neutral Network(NN) has been a good candidate for searching optimal solutions to the constrained shortest routing path in v...Overlay multicast has become one of the most promising multicast solutions for IP network,and Neutral Network(NN) has been a good candidate for searching optimal solutions to the constrained shortest routing path in virtue of its powerful capacity for parallel computation. Though traditional Hopfield NN can tackle the optimization problem,it is incapable of dealing with large scale networks due to the large number of neurons. In this paper,a neural network for overlay multicast tree com-putation is presented to reliably implement routing algorithm in real time. The neural network is constructed as a two-layer recurrent architecture,which is comprised of Independent Variable Neurons(IDVN) and Dependent Variable Neurons(DVN) ,according to the independence of the decision variables associated with the edges in directed graph. Compared with the heuristic routing algorithms,it is characterized as shorter computational time,fewer neurons,and better precision.展开更多
In vehicular networks,the exchange of beacons among neighboring vehicles is a promising solution to guarantee a vehicle's safety.However,frequent beaconing under high vehicle density conditions will cause beacon c...In vehicular networks,the exchange of beacons among neighboring vehicles is a promising solution to guarantee a vehicle's safety.However,frequent beaconing under high vehicle density conditions will cause beacon collisions,which are harmful to a vehicle's driving safety and the location tracking accuracy.We propose an ABIwRC(Adaptive Beaconing Interval with Resource Coordination)method for a highway scenario.Each vehicle broadcasts beacon interval requests,including the intervals needed for both the vehicle's driving safety and location tracking accuracy.The RSU(Road Side Unit)allocates resources for a vehicle's beaconing according to the requests from all vehicles and the interference relationship between the vehicles in adjacent RSUs.We formulate a resource allocation problem for maximizing the sum utility,which measures the satisfaction of vehicles'requests.We then transform the optimization problem into a maximum weighted independent set problem,and propose an algorithm to solve this effciently.Simulation results show that the proposed method outperforms the benchmark in terms of beacon reception ratio,vehicle driving safety,and location tracking accuracy.展开更多
基金the High-tech Project of Jiangsu Province (No.BG2003001).
文摘Overlay multicast has become one of the most promising multicast solutions for IP network,and Neutral Network(NN) has been a good candidate for searching optimal solutions to the constrained shortest routing path in virtue of its powerful capacity for parallel computation. Though traditional Hopfield NN can tackle the optimization problem,it is incapable of dealing with large scale networks due to the large number of neurons. In this paper,a neural network for overlay multicast tree com-putation is presented to reliably implement routing algorithm in real time. The neural network is constructed as a two-layer recurrent architecture,which is comprised of Independent Variable Neurons(IDVN) and Dependent Variable Neurons(DVN) ,according to the independence of the decision variables associated with the edges in directed graph. Compared with the heuristic routing algorithms,it is characterized as shorter computational time,fewer neurons,and better precision.
基金This work is supported in part by the Zhejiang Provincial Public Technology Research of China(No.2016C31063the Fun-damental Research Funds for the Central Universities(No.2015XZZX001-02)a research grant from the Natural Sciences and Engineering Research Council of Canada.
文摘In vehicular networks,the exchange of beacons among neighboring vehicles is a promising solution to guarantee a vehicle's safety.However,frequent beaconing under high vehicle density conditions will cause beacon collisions,which are harmful to a vehicle's driving safety and the location tracking accuracy.We propose an ABIwRC(Adaptive Beaconing Interval with Resource Coordination)method for a highway scenario.Each vehicle broadcasts beacon interval requests,including the intervals needed for both the vehicle's driving safety and location tracking accuracy.The RSU(Road Side Unit)allocates resources for a vehicle's beaconing according to the requests from all vehicles and the interference relationship between the vehicles in adjacent RSUs.We formulate a resource allocation problem for maximizing the sum utility,which measures the satisfaction of vehicles'requests.We then transform the optimization problem into a maximum weighted independent set problem,and propose an algorithm to solve this effciently.Simulation results show that the proposed method outperforms the benchmark in terms of beacon reception ratio,vehicle driving safety,and location tracking accuracy.
